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Experimental study and modeling of cutting force in high-speed milling of Ti-6Al-4V titanium alloy
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Abstract
This study investigates the milling forces involved in high-speed milling of the difficult-to-machine material Ti6Al4V (TC4). A comprehensive analysis of the influence of cutting parameters on milling forces was conducted using a multi-factor orthogonal experiment. The findings revealed that processing such materials is best suited for high-speed milling with shallow cutting depths. To comprehend the milling forces thoroughly, they were decomposed into vertical, horizontal and axial components. By establishing a three-dimensional milling force model using the principles of the least squares method, probabilistic statistical method and regression analysis, we established a relationship between these forces and the cutting parameters. We rigorously tested the significance of regression parameters in the model and performed a thorough analysis of confidence levels and residuals. The results demonstrated that the established model accurately reflected the original experimental data, thus ensuring its reliability in predicting and controlling milling forces. Consequently, this research provides a solid foundation for optimizing parameters in high-speed milling of titanium alloys.
Oxford University Press (OUP)
Title: Experimental study and modeling of cutting force in high-speed milling of Ti-6Al-4V titanium alloy
Description:
Abstract
This study investigates the milling forces involved in high-speed milling of the difficult-to-machine material Ti6Al4V (TC4).
A comprehensive analysis of the influence of cutting parameters on milling forces was conducted using a multi-factor orthogonal experiment.
The findings revealed that processing such materials is best suited for high-speed milling with shallow cutting depths.
To comprehend the milling forces thoroughly, they were decomposed into vertical, horizontal and axial components.
By establishing a three-dimensional milling force model using the principles of the least squares method, probabilistic statistical method and regression analysis, we established a relationship between these forces and the cutting parameters.
We rigorously tested the significance of regression parameters in the model and performed a thorough analysis of confidence levels and residuals.
The results demonstrated that the established model accurately reflected the original experimental data, thus ensuring its reliability in predicting and controlling milling forces.
Consequently, this research provides a solid foundation for optimizing parameters in high-speed milling of titanium alloys.
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